Application of Boolean Networks to discover stem and progenitor cells

项目摘要 我们已经开发了几种新的方法来分析大规模并行基因表达数据集。第一、 StepMiner，一种识别时间进程微阵列数据集中逐步转换的工具。第二，布尔网络， 一种利用这些大量的基因表达发现基因之间布尔含义的方法， 数据集。最近，我们发表了一种名为MiDReG（挖掘发育调节基因）的新方法， 使用布尔蕴涵成功地预测发育途径中的基因。通过最初应用此 在淋巴细胞分化的方法中，我们发现了以前未被认识的B细胞分化的标志物， 也是B细胞和T细胞发育的一个新分支。 该项目将建立在我们成功预测人类B细胞发育基因的基础上， MiDReG开发了一种发现癌症干细胞和祖细胞的通用方法。我打算验证 这种方法在人类膀胱癌（移行细胞癌），首先，因为它是一个简单的模型癌症， 测试，第二，因为我们的实验室具有分离和测试细胞群的专业知识， 潜力该方法将被优化用于发现膀胱癌中的干细胞和祖细胞， 希望它能成为其他类型癌症的类似研究的起点。超过90%的人类 膀胱癌起源于称为尿道上皮的简单上皮组织，通常称为移行上皮癌。 细胞癌（TCC）。此外，人类膀胱癌是美国第五大常见癌症。 本实验室建立了人膀胱癌小鼠异种移植的工作模型 并且最近在膀胱癌中发现了肿瘤起始群体。最近的研究表明，癌症 是异质的，并形成原始肿瘤细胞群的层次结构。然而，详细的膀胱癌 发展层次仍然未知。我在这份提案中的主要近期目标是理解这一点 使用系统生物学方法预测（诊断/预后）基因， 标记特定人群。我将与人癌症组织微阵列合作验证这种方法 与Matt货车de Rijn博士合作，并与Robert Chin和Jens-Peter博士合作使用异种移植 你好。从长远来看，我将扩展该方法，以识别其他类型癌症中的干细胞和祖细胞 在我的独立调查阶段

Project Summary We have developed several novel approaches for analysis of massively parallel gene expression datasets. First, StepMiner, a tool that identifies step-wise transitions in the time course microarray datasets. Second, BooleanNet, a method of discovering Boolean implications between genes using these large numbers of gene expression datasets. Recently, we published a new method called MiDReG (Mining Developmentally Regulated Genes) that uses Boolean implications to successfully predict genes in developmental pathways. By initially applying this approach to lymphocyte differentitaion, we discovered previously unrecognized markers for B cell differentiation, as well as a novel branchpoint of B cell and T cell development. The proposed project will build on our successful prediction of human B cell developmental genes using MiDReG to develop a general method for discovering cancer stem and progenitor cells. I am planning to validate this approach in human bladder cancer (Transitional Cell Carcinoma), first, because it is a simple model cancer to test, and, second, because our laboratory has the expertise to isolate and test cell populations for tumor-initiating potential. This method will be optimized for the discovery of stem and progenitor cells in bladder cancer and hopefully it will serve as a starting point for similar studies in other types of cancers. More than 90% of human bladder cancers arise from a simple epithelial tissue called urothelium, and are commonly called transitional cell carcinomas (TCC). Furthermore, human bladder cancer is fifth most common cancer in the United States. Our laboratory has established a working model for the xenotransplantation of human bladder cancer in mice and has recently discovered a tumor-initiating population in bladder cancer. Recent studies show that cancer is heterogeneous and forms a hierarchy of original tumor cell populations. However, a detailed bladder cancer developmental hierarchy remains unknown. My primary near-term goal in this proposal is to understand this hierarchy of bladder cancer cells using a systems biology approach to predict (diagnostic/prognostic) genes that mark specific populations. I will validate this approach using human cancer tissue microarrays in collaboration with Dr. Matt van de Rijn ,and using xenotransplantation in collaboration with Drs. Robert Chin and Jens-Peter Volkmer. In the longer term, I will extend the method to identify stem and progenitor cells in other types of cancers during my independent investigator phase.